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Welcome to our 11th and 12th Grade Statistics class website!

  • Here you'll find all the resources you need to succeed in this course."
  • Brief introduction about you: "I'm Mrs. Ravi Joshi, and I've been teaching statistics for 10 years. I'm excited to help you explore the fascinating world of data and probability."
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Course Overview

This course will introduce students to the fundamental concepts of statistics, including data collection, analysis, and interpretation. Students will learn how to use statistical methods to make informed decisions based on data.
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Key Topics Covered

Descriptive Statistics: Understanding and summarizing data using measures such as mean, median, mode, and standard deviation. Probability: Exploring the basics of probability theory and how it applies to statistical analysis.
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Learning Objectives

By the end of the course, students will be able to: Analyze and interpret data sets to draw meaningful conclusions. Apply statistical methods to real-world problems. Understand the principles of probability and how they influence statistical reasoning.
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Assessment and Evaluation

Students will be assessed through a combination of homework assignments, projects, quizzes, and exams. Participation in class discussions and activities will also contribute to the overall grade. Regular feedback will be provided to help students improve and succeed in the course.
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Introduction to Statistics
  • Definition and importance of statistics
  • Types of data: Qualitative vs. Quantitative
  • Levels of measurement: Nominal, Ordinal, Interval, Ratio
Descriptive Statistics
  • Measures of central tendency: Mean, Median, Mode
  • Measures of dispersion: Range, Variance, Standard Deviation
  • Data visualization: Histograms, Pie charts, Box plots
Probability
  • Basic probability concepts and rules
  • Conditional probability and independence
  • Probability distributions: Binomial, Normal, and others
Inferential Statistics
  • Sampling methods and sampling distributions
  • Confidence intervals
  • Hypothesis testing: Null and alternative hypotheses, p-values, significance levels
Correlation and Regression
  • Correlation analysis: Pearson and Spearman coefficients
  • Simple linear regression: Model, assumptions, interpretation
  • Multiple regression: Extending to multiple predictors
Advanced Topics (optional)
  • Analysis of variance (ANOVA)
  • Chi-square tests
  • Non-parametric tests
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